Presentation on theme: "Advanced Information Modeling and Database Systems"— Presentation transcript:
1 Advanced Information Modeling and Database Systems Introduction to Database
2 Data, Information, Knowledge, and Wisdom Data: facts concerning people, objects, events or other entitiesStructured: numbers, text, datesUnstructured: images, video, documentsInformation: data that are processed to be useful; answers "who", "what", "where", and "when" questionsKnowledge: the appropriate collection of information, such that it's intent is to be useful; answers "how" questionsUnderstanding: appreciation of “why”Wisdom: evaluated understanding
3 File SystemsTraditionally composed of collection of file folders kept in file cabinetOrganization within folders was based on data’s expected use (ideally logically related)System was adequate for small amounts of data with few reporting requirementsFinding and using data in growing collections of file folders became time consuming and cumbersome
5 File Systems (cont.) Advantages of File Systems No resource overheadNo cost overheadSpeed to access dataDisadvantages of File SystemsData redundancy and inconsistencyDifficulty in access data and process dataLack of standardizationsHard to maintenance and update dataSecurity problems, etc….…
6 Database System and Database Management System (DBMS)
7 Database System (cont.) Shared collection of logically related data (and a description of this data), designed to meet the information needs of an organization.System catalog (metadata, data dictionary) provides description of data to enable program–data independence.Logically related data comprises entities, attributes, and relationships of an organization’s information.
8 Database Management System (DBMS) A software system that enables users to define, create, maintain, and control access to the database.(Database) application program: a computer program that interacts with database by issuing an appropriate request (SQL statement) to the DBMS.
10 Advantages of DBMSs Control of data redundancy Data consistency More information from the same amount of dataSharing of dataImproved data integrityImproved securityEnforcement of standardsEconomy of scaleMultiple applications on 1 set of data
11 Advantages of DBMSs Balance conflicting requirements DBA makes decision about the design and operational use of database in order to achieve the optimal performanceImproved data accessibility and responsivenessIncreased productivityImproved maintenance through data independenceIncreased concurrencyImproved backup and recovery service
12 Disadvantages of DBMSs ComplexitySizeCost of DBMSAdditional hardware costsCost of conversionPerformanceDBMS is written to be more general (as opposed to being specific to a certain type of application), so it may not run as fast as the file-based systems.Higher impact of a failure – single point of failure
14 Database Architecture (cont.) External LevelUsers’ view of the database.Describes that part of database that is relevant to a particular user.Conceptual LevelCommunity view of the database.Describes what data is stored in database and relationships among the data.Internal LevelPhysical representation of the database on the computer.Describes how the data is stored in the database.
15 Differences between Three Levels of ANSI-SPARC Architecture
16 Benefit of 3-level Architecture: Data Independence Logical Data IndependenceCapacity to change conceptual schema without having to change external schema or application programsPhysical Data IndependenceCapacity to change the internal schema without having to change the conceptual (or external) schemas
17 Data Independence and the ANSI-SPARC Three-Level Architecture
18 Data ModelIntegrated collection of concepts for describing data, relationships between data, and constraints on the data in an organization.Data Model comprises:A structural part; which database can be constructedA manipulative part; types of allowed operationA set of integrity rules; ensuring accuracy of data
19 Data Model (Cont.) Purpose Categories of data models include: To represent data in an understandable way.Categories of data models include:PhysicalRecord-basedObject-based
20 Data Model Physical Data Models Record-Based Data Models Hierarchical Data ModelNetwork Data ModelRelational Data ModelObject-Based Data ModelsEntity-Relationship Data ModelObject-Oriented Data Modeletc.
80 Examples of Generalization, Inheritance, and Constraints - a) Employee Superclass with Three SubclassesAn employee can only be one of these subclassesShared attributes and operationsAn employee may be none of themSpecialized attributes and operations
84 Polymorphism, Abstract Operation, Class-Scope Attribute, and Ordering This operation is abstract…it has no method at Student levelClass-scope attributes–only one value common to all instances of these classes (includes default values)Methods are defined at subclass level